The survival of organisms depends on their ability to perceive and respond to extra-cellular signals. At the molecular level, signals are perceived and transmitted through networks of interacting proteins or the like, that act cooperatively to maintain cellular homeostasis and regulate activities like growth, division and differentiation. Information transfer through biological signaling networks is mediated largely by protein-protein interactions that can assemble and disassemble dynamically in response to signals, creating transient circuits that link external events to specific internal outputs, such as changes in gene expression. Numerous strategies have been developed to map the protein-protein interactions that underlie these networks. These studies have collectively provided a wealth of data delineating genome-wide protein-protein interactions for Saccharomyces cervisiae and other organisms. While powerful, these approaches have provided only a partial picture and are likely to overlook many interactions that are context dependent, forming only in the presence of their appropriate signals.
The disruption of protein-protein interactions either by mutation or small-molecules can create biological fulcrums that enable small perturbations of a signaling network to elicit large changes in cellular phenotype. However, not all protein-protein interactions in a given signaling pathway are likely to possess this power. As such, complementary strategies that aim to identify regulatory protein-protein interactions by artificially introducing proteins or peptides into cells which compete with and titrate-out the endogenous regulatory interactions, thereby disrupting the normal circuits that connect external signals to cellular responses, are of interest. By combining this strategy with functional assays, such as the activation of a gene in response to a signal, screens for functional interference can be used to identify peptides that perturb regulatory protein-protein interactions. This strategy, often referred to as dominant-interfering or dominant-negative genetics, has been successfully employed in several model organisms where high-throughput screening methods are easily applied, and to a lesser extent in mammals, which have traditionally been less amenable to these types of screens. One advantage of dominant-negative strategies is that such strategies can pinpoint the functionally relevant protein-protein interaction “fulcrum points” and thereby expose the small number of nodes within the larger web of a protein network that are susceptible to functional modulation by external agents. As such, the results of such strategies can provide vital information about the regulatory components that define a particular pathway and can allow the elucidation of key protein-protein interactions suitable for targeting by drug screening programs.
The difficulty in transfecting cells or producing transgenic organisms hinders the progression of development of dominant negative screening in mammals. To overcome this problem, high-efficiency retrovirus transfection has been developed. Although this retrovirus transfection is potent, it is necessary to produce DNA to be packaged into viral intermediates, and therefore, the applicability of this technique is limited. Alternatively, high-density transfection arrays or cell arrays are being developed, and the use thereof is proposed.
Rosetta Inpharmatics has proposed using cellular information as a profile in some patent applications (Japanese PCT National Phase Laid-Open Publication No.: 2003-505038; Japanese PCT National Phase Laid-Open Publication No.: 2003-505022; Japanese PCT National Phase Laid-Open Publication No.: 2002-533701; Japanese PCT National Phase Laid-Open Publication No.: 2002-533700; Japanese PCT National Phase Laid-Open Publication No.: 2002-533699; Japanese PCT National Phase Laid-Open Publication No.: 2002-528095; Japanese PCT National Phase Laid-Open Publication No.: 2002-526757; Japanese PCT National Phase Laid-Open Publication No.: 2002-518021; Japanese PCT National Phase Laid-Open Publication No.: 2002-518003; Japanese PCT National Phase Laid-Open Publication No.: 2002-514804; Japanese PCT National Phase Laid-Open Publication No.: 2002-514773; Japanese PCT National Phase Laid-Open Publication No.: 2002-514437). In such a profile, information from separate cells is processed as a group of separate pieces of information, but not continuous information. Therefore, this technique is limited in that information analysis is not conducted on a single (the same) cell. Particularly, in this technique, analysis is conducted only at one specific time point before and after a certain change, and a series of temporal changes in a point (gene) are not analyzed.
Recent advances in profiling techniques have led to accurate measurement of cellular components, and thus, profiling of cellular information (e.g., Schena et al., 1995, “Quantitative monitoring of gene expression patterns with a complementary DNA microarray”, Science 270:467-470; Lockhart et al., 1996, “Expression monitoring by hybridization to high-density oligonucleotide arrays”, Nature Biotechnology 14:1675-1680; Blanchard et al., 1996, “Sequence to array: Probing the genome's secrets”, Nature Biotechnology 14:1649; and U.S. Pat. No. 5,569,588). For organisms whose genome is entirely known, it is possible to analyze the transcripts of all genes in a cell. In the case of other organisms, for which the amount of known genomic information is increasing, a number of genes in a cell can be simultaneously monitored.
As array technology advances, arrays also have been utilized in the field of drug screening (e.g., Marton et al., “Drug target validation and identification of secondary drug target effects using Microarrays”, Nat. Med., 1998 November, 4(11):1293-301; and Gray et al., 1998, “Exploiting chemical libraries, structure, and genomics in the search for kinase inhibitors”, Science, 281:533-538). Analysis using profiles (e.g., U.S. Pat. No. 5,777,888) and clustering of profiles provides information about conditions of cells, transplantation, target molecules and drug candidates, and/or the relevant functions, efficacy and toxicity of drugs. These techniques can be used to determine a common profile which represents ideal drug activity and disease conditions. Comparing profiles assists in detecting diseases in patients at an early stage, and provides prediction of improved clinical outcomes for patients who have been diagnosed as having a disease.
However, to date, there has been no technique which can provide information about the same cell in the true sense. In the above-described techniques, data is obtained as average for a group of heterologous cells. Analyses and evaluations based on such data lack accuracy. Therefore, there is an increasing demand for a method of providing information at the cellular level.
An object of the present invention is to provide a method for obtaining information, profiles or data of a cell. Another object of the present invention is to provide a method for obtaining information and data relating to cell status in a consistent environment, and a method and system for accurately presenting such data. In particular, a particular purpose of the present invention is to provide a system and a method for directly or as such information of a cell in a consistent environment in terms of complex system information, and providing such data and data sequencing technology per se. Another object of the present invention is to provide a digital cell and uses thereof.